Assumptions inherent in prediction of fat from skinfolds
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Assumptions inherent in prediction of % Fat from Skinfolds. Based upon densitometry. “Which is better UW Weighing or Skinfold predictions?” %fat from skinfolds is predicted using equations developed from UW Weighing of subjects.

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Assumptions inherent in prediction of % Fat from Skinfolds

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Assumptions inherent in prediction of fat from skinfolds

Assumptions inherent in prediction of % Fat from Skinfolds

  • Based upon densitometry

“Which is better UW Weighing or Skinfold predictions?”

%fat from skinfolds is predicted using equations developed from UW Weighing of subjects.

UW Weighing: S.E.E. = 2.77% Fat Skinfolds: S.E.E. = 3.7% Fat


Assumptions inherent in prediction of fat from skinfolds1

Assumptions inherent in prediction of % Fat from Skinfolds

  • Constant Skinfold Patterning

  • Constant Skinfold Compressibility

  • Constant Tissue Densities

  • Constant Ratio of external/internal adipose tissue

  • Constant Fat (lipid) content of adipose tissue


Yuhasz

YUHASZ

Male: % Fat = 0.1051(Sum 6 SF) + 2.585

Female:% Fat = 0.1548(Sum 6 SF) + 3.580

Canadian University Students

Can never give a negative answer.

What if weight alone changes or is different?


Durnin womersley

Durnin & Womersley

  • Density = a (log10Sum 4 SF) + c

  • Overpredicts by 3 - 5% Fat

  • British (left side)

  • Age and gender specific equations

  • Upper body sites

  • Electronic Skinfold Caliper


Ultrasound

Ultrasound

High Frequency Sound (6 MHz)

Some sound reflected at tissue interfaces

Time taken for return of sound used to estimate distance based upon assumed speed of sound in that tissue


Fat prediction from ultrasound

% Fat prediction from Ultrasound

  • Regression equations predicting densitometrically determined % Fat

  • S.E.E.’s comparable to skinfold predictions

  • Beware of “predict anything from anything” once it is in a computer


Radiography

RADIOGRAPHY

  • Measurements from radiographs

    • uncompressed tissue thicknesses

  • Regression equations predicting densitometrically determined % Fat

  • Not used any more due to possible negative health consequences


Bioelectrical impedance analysis bia

BIOELECTRICAL IMPEDANCE ANALYSIS (BIA)

  • BIA measured by passing a microcurrent through the body

  • % Fat predicted from sex, age, height, weight & activity level + BIA

  • Influenced by hydration level

  • Claims that you can guess % fat more accurately


Typical bia equations

Typical BIA Equations

  • Males

    • FFM = -10.68 + 0.65H2/R + 0.26W + 0.02R

  • Females

    • FFM = -9.53 + 0.69H2/R + 0.17W + 0.02R

  • Where

    • FFM = fat free mass (kg)

    • H = height (cm)

    • W = body weight (kg)

    • R – resistance (ohms)

  • % BF = 100 x (BW-FFM)/BW


Major types of bia analyzers

Major types of BIA analyzers


Client friendly

Client Friendly


Site specific

Site Specific?


Bia protocol

BIA Protocol

  • Very sensitive to changes in body water

    • normal hydration

      • caffeine, dehydration, exercise, edema, fed/fasted

  • Sensitive to body temperature

    • Avoid exercise

  • Sensitive to placement of electrodes

    • conductor length vs. height


Near infra red spectrophotometry nir futrex

Near Infra-Red Spectrophotometry (NIR)FUTREX

  • Near Infra-Red light emitted from probe

  • Reflected light monitored

  • Changes due to differing optical densities

  • Influenced by hydration

  • Relative fat may be useful


Dual energy x ray absorptiometry

Dual-Energy X-ray Absorptiometry


Dexa dxa d ual e nergy x ray a bsorptiometry

DEXA, DXADual Energy X-ray Absorptiometry

  • Two different energy level X-rays

  • Lean, fat, and bone mass each reduce (attenuate) the X-ray signal in unique ways

  • Whole body

  • Regional

  • Osteoporosis


Assumptions inherent in prediction of fat from skinfolds

BMI = 12.6

%Fat = 3.2%

BMI = 23.7

%Fat = 48.1%

BMI = 18.1

%Fat = 23.1%


Assumptions inherent in prediction of fat from skinfolds

What DEXA Measures

  • Fat and fat-free mass (based upon the standards)

  • Bone Mineral Mass

  • Regional results for the above


Assumptions inherent in prediction of fat from skinfolds

DEXA Cannot Measure...

  • Protein Mass

  • 3-D Fat Distribution

  • Hydration Status

  • Tissue inside bone (brain, marrow, blood)


Next generation of body composition models

Next generation of Body Composition Models

  • Two compartment plus

    • Water

    • Bone mineral

    • Protein

  • 3 or 4 compartment models now regarded as the reference standard rather than underwater weighing


Validation of methods of estimating body fat

Validation of Methods of Estimating % Body Fat


How do you validate these techniques

  • There can be no direct validation

    • Measure subjects with technique to get % fat then kill them, blend them and dissolve out lipid

  • Validation of Indirect techniques is by comparison to other Indirect techniques

  • Which analysis indicates validity

    • Correlation

    • Test of Difference of means between tests

    • Linear regression – slope of unity

    • Standard Error of Estimate

How do you validate these techniques?


Regression equations to predict body fat

Regression Equationsto Predict % Body Fat

Y = mX + c

Y = % Body Fat

X = Anthropometric measure (Skinfolds etc)

Correlation Coefficient (r)

Standard Error of Estimate (SEE)


Predicting fat from density

Predicting % Fat from Density

ASSUMPTIONS

Body can be divided into two components:

Fat & Non-Fat (Fat Free) Masses

Each has different, known and constant densities


Siri equation

SIRI EQUATION

Assumptions:

Density of FAT MASS0.9 gm/ml

Density of NON-FAT MASS 1.1 gm/ml

Equation:

% Fat = (4.95/Density)-4.5) x 100


Brozek equation

BROZEK EQUATION

Assumptions:

Density of FAT MASS0.9 gm/ml

Density of LEAN BODY MASS 1.095 gm/ml

(some essential lipids in Lean Body Mass)

Equation:

% Fat = (4.57/Density)-4.142) x 100


Assumptions inherent in prediction of fat from skinfolds

Siri Equation: % Fat = (4.95/Density)-4.5) x 100


Error in prediction of fat

Error in Prediction of % Fat

Standard Error of Estimate

for % Fat from Densitometry

S.E.E.=2.77% Body Fat

due to variation in density of fat free mass

Example:

predicted value = 15% Body Fat

95% confidence in true value = 15 ± 1.96 x S.E.E.

= 15 ± (1.96 x 2.77) = 9.57% - 20.43%


Assumptions inherent in prediction of fat from skinfolds

Obvious Errors

In 9 of 29 measured, the density of FFM was clearly not 1.1 gm/ml


Variability of constants

Variability of Constants

  • The existence of this table infers that we should know the precise density of FFM.

  • However, using arbitrary cut-offs between age groups merely highlights the problem


Assumptions inherent in prediction of fat from skinfolds

DEXA vs. Hydro-Densitometry


Bodpod vs dexa fields et al 2002

  • “SEEs ranged from 2.4% to 3.5% BF”?

    • “which were distributed among the good, very good, and excellent categories, as subjectively assessed by Lohman (1992)”

  • SEE = 4.1% BF gives

    • 95% confidence of ± 1.96 x 4.1%BF

    • 95% confidence of ± 8%BF !!!!!!

BODPOD vs DEXAFields et al. 2002


The new york obesity research center

The New York Obesity Research Center

  • The assumed density of 1.1 g/cm3 is based on observations made in a limited number of human cadavers suggesting relatively stable proportions of water, protein, glycogen and minerals. To the extent that these proportions change in any individual subject will introduce corresponding errors in the assumed density of fat-free mass.

  • A number of studies suggest that the density of fat-free mass is relatively stable across age and sex groups, although some variation is recognized at the extremes of age and in patients who have underlying medical and surgical conditions. NOT TRUE!!!

  • Additionally, there may exist race differences in the density of fat-free mass as well as variation among special groups such as body builders or other types of athletic participants. Thus, while underwater weighing and the two-compartment model served as a reference technique for several decades, newer approaches without these various assumptions are now replacing hydrodensitometry as the clinical reference method. MISLEADING!!!


Beware of garbage

Beware of Garbage

  • BIA (Bioelectrical Impedance) - The only method that is based on measuring something, not estimating anything, is Bio-Impedance measurement. Bio-Impedance is a means of measuring electrical signals as they pass through the fat, lean mass, and water in the body. Through laboratory research we know the actual impedance or conductivity of various tissues in the body, and we know that by measuring current between two electrodes and applying this information to complex proven scientific formulas accurate body composition can be determined. The fact that the measurement is based on a reading of lean mass and not an estimate of fat mass, lends to a much more comprehensive testing method and results.


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